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An Optimization Model for Operations of Large scale Hydro Power Plants

IEEE LATIN AMERICA TRANSACTIONS 2020年第9期18卷 1631-1638页

作者： Alvarez, Gonzalo E. INGAR CONICET UTN Inst Desarrollo & Diseno Avellaneda 3657 Santa Fe Argentina

Globally, there is an increase in the proportion of renewable sources for electricity generation. Among renewable sources, hydropower is the most widespread. For this reason, the improvements of their applications have been the focus of researches. Hydroelectric power plants have numerous aspects which might represent several economic advantages, if they are operated efficiently. Mathematical optimization models are interesting tools that help in the decision-making processes. In this context, this paper introduces a new mixed integer Lineal programming model that determines the most convenient combination of units to operate a large-scale hydro power plant. Several aspects of reality are taken into account, which are sometimes not considered, such as the variation of the hydraulic head and the performance of other elements besides the turbines, as floodgates. To prove the effectiveness of the new model, the Itaipu Power Plant is selected as a case study. It has an installed power capacity of 14,000 MW and holds the world record in terms of annual generation with 103 million MWh. Three possible scenarios are evaluated in order to analyze the behavior of this plant in normal and extreme situations. The results indicate that the model effectively reduces computational times, and that power generation is influenced by market price variations and reservoir limitations..

关键词： Computational modeling Optimization Silicon compounds Mathematical model IEEE transactions Hydroelectric power generation Hydraulic systems Itaipú Hydraulic Head Operating Curves Electric Power Generation mixed integer linear programming

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Regional integrated energy system energy management in an industrial park considering energy stepped utilization

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ENERGY 2020年 201卷

作者： Zhu, Xu Yang, Jun Pan, Xueli Li, Gaojunjie Rao, Yingqing Wuhan Univ Sch Elect Engn & Automat Wuhan 430072 Peoples R China State Grid Hubei Elect Power Co Wuhan 430077 Peoples R China

There are multiple energy demands in industrial parks. The industrial park's energy system includes a variety of energy sources and energy-consuming equipment, with diverse load types and high reliability requirements for power supplies. And the situation of low energy utilization rates, unreasonable energy structures, great peak-to-valley power differences and the environment pollution needs to be improved. The application of multi-energy complementary regional integrated energy systems (RIES) can improve the performance of the industrial parks. Considering reasonable correspondence between the energy supply and demand in RIES, this paper proposes an RIES energy management strategy based on energy stepped utilization to further minimize the daily cost and make full use of the energy. Additionally, the piecewise linear model of gas turbine is established considering a part load ratio. According to the grade demands, the heat loads are divided into high-grade, middle-grade and low-grade heat loads and the load models are respectively established. The scenario reduction method is used to obtain typical scenarios in order to describe the randomness of weather factors. Finally, the simulation analysis shows that the proposed energy management method for the RIES can arrange the combination of gas turbines and output of devices more flexibly, and a more economical scheduling plan can be provided by this method. The high-grade and middle-grade energy are not only supplied to corresponding loads, but also can be converted into low-grade energy. Additionally, the stability and energy efficiency of the system are improved with the application of this strategy. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Regional integrated energy system Stepped utilization of energy mixed integer linear programming Industrial park Economic dispatching

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A linear Relaxation-Based Heuristic for Iron Ore Stockyard Energy Planning

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ENERGIES 2020年第19期13卷

作者： Jesus Servare Junior, Marcos Wagner de Oliveira Rocha, Helder Roberto Felix Salles, Jose Leandro Perron, Sylvain Univ Fed Espirito Santo Dept Elect Engn Ave Fernando Ferrari514 Goiabeiras BR-29075910 Vitoria ES Brazil Hautes Etud Commerci Montreal Grp Res Decis Anal 3000 Chemin Cote St Catherine Montreal PQ H3T 2A7 Canada

Planning the use of electrical energy in a bulk stockyard is a strategic issue due to its impact on efficiency and responsiveness of these systems. Empirical planning becomes more complex when the energy cost changes over time. The mathematical models currently studied in the literature consider many actors involved, such as equipment, sources, blends, and flows. Each paper presents different combinations of actors, creating their own transportation flows, thus increasing the complexity of this problem. In this work, we propose a new mixed integer linear programming (MILP) model for stockyard planning solved by a linear relaxation-based heuristic (LRBH) to minimize the plan's energy cost. The proposed algorithm will allow the planner to find a solution that saves energy costs with an efficient process. The numerical results show a comparison between the exact and heuristic solutions for some different instances sizes. The linear relaxation approach can provide feasible solutions with a 3.99% average distance of the objective function in relation to the optimal solution (GAP) in the tested instances and with an affordable computation time in instances where the MILP was not able to provide a solution. The model is feasible for small and medium-sized instances, and the heuristic proposes a solution to larger problems to aid in management decision making.

关键词： heuristic methods iron ore stockyard energy planning linear relaxation-based heuristic mixed integer linear programming

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Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements

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ENERGIES 2020年第16期13卷

作者： Micangeli, Andrea Fioriti, Davide Cherubini, Paolo Duenas-Martinez, Pablo Sapienza Univ Rome Dept Mech & Aerosp Engn DIMA Via Eudossiana 18 I-00184 Rome Italy Univ Pisa Dept Energy Syst Terr & Costruct Engn DESTEC I-56122 Pisa Italy MIT MIT Energy Initiat 77 Massachusetts Ave Cambridge MA 02139 USA

The lack of electricity access is increasingly concentrated in rural areas of developing countries, in which mini-grids are often a suitable solution;however, given the high risks, it is crucial to minimize costs. This paper aims at analyzing existing methodologies for the optimal design of mini-grids combined with different operating strategies. Typical system operations, like the load-following (LFS) and cycle charging (CCS) strategies, are compared with the more demanding predictive strategies based on mixed-integer linear programming (MILP). The problem is formulated and solved with Particle Swarm Optimization (PSO), so to simulate traditional and predictive operating strategies. Two reformulations based on the proposed Search Space Update are also detailed and compared with the so-called one-shot MILP model, which is able to con-jointly optimize both the design and the operation of the system, in order to reduce computational requirements with the predictive strategy. The results, tailored with data from a rural mini-grid in Kenya, highlight that heuristic methodologies can perform better than the traditional MILP approach, both in terms of optimality and computational time, especially when advanced operating strategies are considered. Conventional operating strategies (LFS or CCS) appear to be sub-optimal, but require very little computational requirements, which makes them suitable for preliminary designs.

关键词： isolated hybrid system microgrids mixed integer linear programming off-grid energy system Search Space Update (SSU)

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Data-Driven Event Diagnosis in Transmission Systems With Incomplete and Conflicting Alarms Given Sensor Malfunctions

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IEEE TRANSACTIONS ON POWER DELIVERY 2020年第1期35卷 214-225页

作者： Jiang, Yazhou Srivastava, Anurag K. Washington State Univ Pullman WA 99164 USA GE Global Res Ctr Niskayuna NY 12309 USA

Accurate fault event diagnosis with incomplete and conflicting alarms given sensor malfunctions is a challenging problem for power system operators. To solve this problem, this study proposes a data-driven approach based on mixed integer linear programming (MILP) for fast determination of fault event scenarios with uncertainties. The uncertainties include failures and malfunction of relays and circuit breakers (CBs) as well as incomplete/incorrect sensor alarms at the control center. To improve the accuracy for fault event diagnosis, redundant alarms from multiple sources, i.e., Phasor Measurement Units (PMUs), Supervisory Control and Data Acquisition (SCADA), and Sequence of Events Recorders (SERs) are jointly used in this study. The temporal correlation of sensor alarms is incorporated in the constraints of the MILP model. The resulting data-driven algorithm determines the most credible fault scenario that is well supported by the available sensor alarms at the control center. Simulation results of the IEEE 14-bus system, the synthetic South Carolina 500-bus system, and a real-world complex event scenario demonstrate the effectiveness of the proposed approach for accurate and efficient fault event diagnosis.

关键词： Alarm message analytical model data-driven fault diagnosis mixed integer linear programming outage management power system protection

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A modified genetic algorithm for non-emergency outpatient appointment scheduling with highly demanded medical services considering patient priorities

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 139卷

作者： Alizadeh, Reza Rezaeian, Javad Abedi, Mehdi Chiong, Raymond Mazandaran Univ Sci & Technol Dept Ind Engn POB 734 Babol Sar Mazandaran Iran Univ Newcastle Sch Elect Engn & Comp Callaghan NSW 2308 Australia

This paper presents an optimization problem concerning the booking of non-emergency outpatient appointments, where a single machine (device) and limited medical staff are supposed to fulfill the medical requirements of a large number of waiting patients. A new mixed integer linear programming model is formulated, characterized by two main features: (1) the method applied to calculate the duration of every single appointment is based on patients' particular therapy requirements and doctors' operating speeds, where the duration of the appointments may be different;and (2) taking the priorities of patients into consideration as a key factor of scheduling in the form of the times they prefer to be booked. The proposed model is solved and evaluated using an exact solver on several small-scale numerical examples, and the optimal solutions show that the model is well-designed and accurate. For instances of larger scale, a genetic algorithm (GA) is used to solve them. The performance of the GA is analyzed by comparing it to the exact method using a set of defined examples. Results indicate that the GA performs satisfactorily within reasonable computational time.

关键词： Appointment scheduling Operations research in health services Non-emergency outpatients mixed integer linear programming Genetic algorithm

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A compact mixed integer linear formulation for safe set problems

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OPTIMIZATION LETTERS 2020年第8期14卷 2127-2148页

作者： Hosteins, Pierre Univ Gustave Eiffel ESTAS COSYS IFSTTAR F-59650 Lille France

The Safe Set Problem is a type of partitioning problem with particular constraints on the weight of adjacent partition components. Several theoretical results exist in the literature along with a mixed integer linear formulation. We propose a new, more compact, mixed integer linear Program for the (Weighted) Safe Set Problem and Connected Safe Set Problem with a polynomial number of variables and constraints, based on a flow from an additional fictitious node. The model is enriched by symmetry-breaking considerations and a variable reduction subproblem. We test the model on a benchmark of small instances which underline the difficulty of solving the Safe Set Problem through mathematical programming approaches. We also compare it with the only existing formulation in the literature and find that our approach is usually more efficient on a set of benchmark instances.

关键词： Graph partitioning Network control Safe set Connected safe set mixed integer linear programming Symmetry-breaking Variable reduction

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Multi-objective optimization in real-time operation of rainwater harvesting systems

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EURO JOURNAL ON DECISION PROCESSES 2023年 11卷

作者： Zhen, Yi Smith-Miles, Kate Fletcher, Tim D. Burns, Matthew J. Coleman, Rhys A. Univ Melbourne Sch Math & Stat Parkville Vic 3010 Australia Univ Melbourne Sch Ecosyst & Forest Sci Parkville Vic 3010 Australia Melbourne Water 990 La Trobe St Docklands Vic 3008 Australia

Increased population growth and urbanization have brought critical challenges to urban water systems, including water scarcity and environmental degradation. To address the problems, real-time controlled rainwater storages are now being used to reduce flooding by intercepting rainfall, while also providing an alternate water supply and actively restoring baseflow to improve biodiversity outcomes. These benefits can be enhanced when the storages are managed as an optimized network. This paper proposes a multi-objective-optimization-based strategy utilizing mixed integer linear programming and compromise programming to control a network of rainwater storages. The proposed strategy is observed to substantially reduce storage overflow, improve stream baseflow, and fulfill most of the domestic non-potable water demand. It shows a clear advantage over the NSGA II-based strategy, indicating the effectiveness of mathematical programming with scalarization techniques in solving multi-objective problems.

关键词： multi-objective optimization water resource management receding horizon approach rainwater harvesting system mixed integer linear programming compromise programming

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Decision regions and decision boundaries of generalizedKmean algorithm based on various norm criteria

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MULTIMEDIA TOOLS AND APPLICATIONS 2020年第41-42期79卷 30669-30684页

作者： Wang, Xinpeng Ling, Bingo Wing-Kuen Guangdong Univ Technol Fac Informat Engn Guangzhou 510006 Peoples R China

This paper derives the decision regions and the decision boundaries of the generalizedKmean algorithms based on theL(1)norm criterion, theL(2)norm criterion and theL(infinity)norm criterion. The decision boundaries of these three generalizedKmean algorithms are all linear hyperplanes. However, the total numbers of the decision boundaries of the generalizedKmean algorithms based on both theL(1)norm criterion and theL(infinity)norm criterion are more than that based on theL(2)norm criterion. On the other hand, the decision regions of the generalizedKmean algorithm based on theL(2)norm criterion are convex while that based on both theL(1)norm criterion and theL(infinity)norm criterion are in general nonconvex. The computer numerical simulations on a toy example demonstrate the above phenomena. Besides, two examples are illustrated. The first example on the patent image retrieval system shows that the recognition accuracies of using the generalizedKmean algorithms based on theL(2)norm criterion, theL(1)norm criterion and theL(infinity)norm criterion are 58.25%, 61% and 58.75%, respectively. The second example on the electromyogram based Parkinson's disease detection system shows that the recognition accuracies of using the generalizedKmean algorithms based on theL(2)norm criterion, theL(1)norm criterion and theL(infinity)norm criterion are 60%, 60% and 67%, respectively, if the signals are classified directly in the time domain. On the other hand, the recognition accuracies of the generalizedKmean algorithms based on theL(2)norm criterion, theL(1)norm criterion and theL(infinity)norm criterion are 60%, 87% and 60%, respectively, if the signals are classified directly in the discrete cosine transform domain. The improvements are due to the nonconvexity of the decision regions of the generalizedKmean algorithm based on theL(1)norm criterion and theL(infinity)norm criterion.

关键词： GeneralizedKmean algorithms Decision regions Decision boundaries Nonconvex set mixed integer quadratic programming mixed integer linear programming

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Power management of grid-integrated energy storage batteries with intermittent renewables

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JOURNAL OF ENERGY STORAGE 2020年 31卷

作者： Al Essa, Mohammed Jasim M. Univ Kufa Fac Engn POB 21 Najaf Governorate Iraq

Intensive charging and discharging modes of batteries cause an adverse effect on state of health of grid-integrated energy storage batteries (GIESBs). Furthermore, uncoordinated patterns of charging and discharging the GIESBs are able to expand voltage profiles of power grids beyond their limits, while considering extra generation from photovoltaic arrays (PVs) and wind turbines (WTs). Therefore, a decentralized power management scheme is proposed in this paper to mitigate such impact on grid voltages and to improve the performance of the GIESBs with PVs and WTs. The proposed scheme develops three clusters of different objective functions to coordinate charging and discharging cycles of the GIESBs based on mixed integer linear programming, considering state of charge (SoC) and depth of discharge (DoD) of the batteries. The first cluster minimizes the power-charging cost of the GIESBs by utilizing time of use tariffs. The second cluster minimizes the charging power of the GIESBs, employing per unit generation from PVs and WTs, whereas the third cluster minimizes the discharging power of the GIESBs, using per unit consumption of residential loads. Simulation results of six scenarios show that, although the proposed scheme of the first cluster reduces operational costs of the GIESBs, it cannot maintain system voltages within the limitations. With the second and third clusters, the proposed scheme exhibits a better performance in stabilizing grid voltages, while maintaining the SoC and DoD within their boundaries to underpin state of health of the batteries.

关键词： Battery energy storage systems Electricity grids mixed integer linear programming Photovoltaic and wind generation Power flow Time of use and feed in tariffs

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